Call-center is a general term used in relation to help desks, information lines and customer service centers. Many companies today operate call-centers to handle a diversity of customer issues. Such may include product and services related issues and grievance redress. Call-centers are constantly trying to increase customer satisfaction and call handling efficiency by aiding agents and agent monitoring.
Call-centers may use a dialog-based support, relying on voice conversations and on line chat, and email support where a user communicates with a professional agent via email. A typical call-center agent handles over a hundred calls in a day. These calls are typically recorded. As a result, gigabytes of data are produced every day in the form of speech audio, speech transcripts, email etc. This data is valuable for doing analysis at many levels. For example, the data may be used to obtain statistics about the type of problems and issues associated with different products and services. The data may also be used to evaluate call center agents and train the agents to improve their performance.
Today's call-centers handle a wide variety of domains, such as computer sales and support, mobile phones, apparel, care rental, etc. To analyze the calls in any domain, analysts need to identify the key issues in the domain. Further, there may be variations within a domain based on the service providers. An example of a domain where variations within the domain exist that are based on the service providers is the domain of mobile phones.
In the past an analyst would generate a domain model through manual inspection of the data. Such a domain model can include a listing of the call categories, types of problems solved in each category, listing of the customer issues, typical question-answers, appropriate call opening and closing styles etc. In essence, these domain models provide a structured view of the domain.
Manually building such domain models for various domains may become prohibitively resource intensive. Many of the domain models are also dynamic in nature and therefore change over time. For example, when a new version of a mobile phone is introduced, when a new software product is launched in a country, or when a new computer virus starts an attack, the domain model may need to be refined.
In view of the foregoing, a need exists for an automated approach of creating and maintaining domain models.